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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

Studies of recognition with multitemporal remote sensor data

Characteristics of multitemporal data and their use in recognition processing were investigated. Principal emphasis was on satellite data collected by the LANDSAT multispectral scanner and on temporal changes throughout a growing season. The effects of spatial misregistration on recognition performance with multitemporal data were examined. A capability to compute probabilities of detection and false alarm was developed and used with simulated distributions for misregistered pixels. Wheat detection was found to be degraded and false alarms increased by misregistration effects. Multitemporal signature characteristics and multitemporal recognition processing were studied to gain insights into problems associated with this approach and possible improvements. Recognition performance with one multitemporal data set displayed marked improvements over results from single-time data.

Malila, W. A.↗
NASA NTRS2010

Considerations for Architecture Level Trade Studies for Environmental Sensors

Comparisons of key characteristics of environmental sensors such as technology readiness levels, mass, power, volume, and detection capabilities are essential for initial trade studies to determine likely candidates for further development and evaluation. However, these trade studies only provide part of the information necessary to make selection decisions. Ultimately, the sensors must be judged based on the overall system architectures and operational scenarios for which they are intended. This means that additional characteristics, such as architectural needs for redundancy, operational lifetime, ability to maintain calibration, and repair and replacement strategies, among others, must also be considered. Given that these characteristics can be extremely time-consuming and costly to obtain, careful planning is essential to minimize the effort involved. In this paper, an approach is explored for determining an effective yet comprehensive set of architecture level trades which is minimally impacted by the inevitable changes in operational (mission) scenarios. The approach will also identify and integrate the various facilities and opportunities required to obtain the desired architecture level trade information.

Peterson, Craig↗
DOE OSTI2021

Thin-Entrance Window Process for Soft X-Ray Sensors

New free electron lasers, such as SLAC’s LCLS-II, will provide unique scientific imaging opportunities. In order to fully utilize these facilities, we need to develop detectors with shallow entrance windows that will enable detection of soft x-rays from 250 eV to 1.5 KeV. Achieving adequately shallow entrance windows is challenging because the high temperature anneal needed to activate the dopant also drives the dopant profile deeper, growing the region that is insensitive to soft x-rays. A new microwave annealing technology provides an efficient way to achieve shallow entrance windows in fully depleted high-resistivity silicon sensors. The microwave anneal technique can activate dopants at low substrate temperature, with minimal dopant diffusion, and can be used to fabricate both n-type and p-type entrance windows. SRP and SIMS measurements were used to verify dopant activation with negligible dopant diffusion. We then applied the microwave anneal process to a planar sensor wafer, using the new process to create the backside diode contact. Electrical test of the resulting sensors shows good reverse bias characteristics. The sensors have been bump-bonded to a read-out ASIC and used successfully to measure an Fe-55 x-ray spectrum. Process and device simulations were performed to characterize the quantum efficiency of the entrance window for soft x-rays. This technique is useful for other sensor applications requiring a shallow entrance window, including detectors for UV photons, low energy ions and low energy electrons.

47 OTHER INSTRUMENTATION↗
NASA NTRS2005

Effects of Piezoelectric (PZT) Sensor Bonding and the Characteristics of the Host Structure on Impedance Based Structural Health Monitoring

This study was conducted to investigate the effects of certain factors on the impedance signal in structural health monitoring. These factors were: the quality of the bond between the sensor and the host structure, and the characteristics of the host structure, such as geometry, mass, and material properties. This work was carried out to answer a set of questions, related to these factors, that were developed by the project team. The project team was comprised of Dr. Doug Ramers and Dr. Abdul Jalloh of the Summer Faculty Fellowship Program, Mr. Arnaldo Colon- Perez, a student intern from the University of Puerto Rico of Turabo, and Mr. John Lassiter and Mr. Bob Engberg of the Structural and Dynamics Test Group at NASA Marshall Space Flight Center (MSFC). This study was based on a review of the literature on structural health monitoring to investigate the factors referred to above because there was not enough time to plan and conduct the appropriate tests at MSFC during the tenure of the Summer Faculty Fellowship Program project members. The surveyed literature documents works on structural health monitoring that were based on laboratory tests that were conducted using bolted trusses and other civil engineering type structures for the most part. These are not the typical types of structures used in designing and building NASA s space vehicles and systems. It was therefore recommended that tests be conducted using NASA type structures, such as pressure vessels, to validate the observations made in this report.

Jalloh, Abdul↗
DOE OSTI2021

Inferring UAV Position Relative to Smartphone Sensor Based on Acoustic Characteristics

As commercial and non-commercial unmanned aerial vehicles (UAVs) improve technologically and increase in accessibility, their potential for use in actions antithetical to nuclear non-proliferation efforts increases as well. The ability to identify and locate UAVs using ubiquitous, inexpensive hardware and software would be advantageous as both a deterrent and an initial warning system. Our team looks to utilize smartphones as acoustic sensors to record and characterize UAV movement based on the sound produced while in flight. Multi-rotor UAVs produce identifiable acoustic spectral characteristics with frequencies and harmonics corresponding to motor revolutions per minute and the propeller characteristics. As the source moves closer to the receiver these spectral patterns remain relatively stable (at slow speeds), while the energy observed from the waves increases. The goal of this work is to utilize a small network of smartphone sensors with known, fixed positions to infer the relative position of an in-flight UAV with respect to the position of the smartphones through the variation in acoustic energy.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
NASA NTRS2011

The 13 years of TRMM Lightning Imaging Sensor: From Individual Flash Characteristics to Decadal Tendencies

How often lightning strikes the Earth has been the object of interest and research for decades. Several authors estimated different global flash rates using ground-based instruments, but it has been the satellite era that enabled us to monitor lightning thunderstorm activity on the time and place that lightning exactly occurs. Launched into space as a component of NASA s Tropical Rainfall Measuring Mission (TRMM) satellite, in November 1997, the Lighting Imaging Sensor (LIS) is still operating. LIS detects total lightning (i.e., intracloud and cloud-to-ground) from space in a low-earth orbit (35deg orbit). LIS has collected lightning measurements for 13 years (1998-2010) and here we present a fully revised and current total lightning climatology over the tropics. Our analysis includes the individual flash characteristics (number of events and groups, total radiance, area footprint, etc.), composite climatological maps, and trends for the observed total lightning during these 13 years. We have identified differences in the energetics of the flashes and/or the optical scattering properties of the storms cells due to cell-relative variations in microphysics and kinematics (i.e., convective or stratiform rainfall). On the climatological total lightning maps we found a dependency on the scale of analysis (resolution) in identifying the lightning maximums in the tropics. The analysis of total lightning trends observed by LIS from 1998 to 2010 in different temporal (annual and seasonal) and spatial (large and regional) scales, showed no systematic trends in the median to lower-end of the distributions, but most places in the tropics presented a decrease in the highest total lightning flash rates (higher-end of the distributions).

Albrecht, R. I.↗
NASA NTRS1983

Operational characteristics of the dispersed sensor processor mesh

The dispersed sensor processing mesh (DSPM) is part of an experimental system used to pursue a proof of concept for an advanced fault-tolerant communication strategy. The DSPM experiments incorporate sensors and effectors into an ultra-reliable nodal network in which a central bus controller performs algorithms to grow and maintain the network. The experiments demonstrate that DSPM is an achievable communication network that can sustain failures and continue to function properly. The results of the experiment give insights into the unique characteristics of the DSPM network and the network's capacity to limit physical damage propagation, limit damaged-data propagation, and to survive cyclic communication paths. This paper describes the concept, mechanization, and performance of the DSPM system in a real-time flight-critical environment.

Abbott, L. W.↗
NASA NTRS1992

The trade-off characteristics of acoustic and pressure sensors for the NASP

Results of a trade study for the development of pressure and acoustic sensors for use on the National Aerospace Plane (NASP) are summarized. Pressure sensors are needed to operate to 100 psia; acoustic sensors are needed that can give meaningful information about a 200 dB sound pressure level (SPL) environment. Both sensors will have to operate from a high temperature of 2000 F down to absolute zero. The main conclusions of the study are the following: (1) Diaphragm materials limit minimum size and maximum frequency response attainable. (2) No transduction is available to meet all the NASP requirements with existing technology. (3) Capacitive sensors are large relative to the requirement, have limited resolution and frequency response due to noise, and cable length is limited to approximately 20 feet. (4) Eddy current sensors are large relative to the requirement and have limited cable lengths. (5) Fiber optic sensors provide the possibility for a small sensor, even though present developments do not exhibit that characteristic. The need to use sapphire at high temperature complicates the design. Present high temperature research sensors suffer from poor resolution. A significant development effort will be required to realize the potential of fiber optics. (6) Short-term development seems to favor eddy current techniques with the penalty of larger size and reduced dynamic range for acoustic sensors. (7) Long-term development may favor fiber optics with the penalties of cost, schedule, and uncertainty.

Winkler, Martin↗
DOE OSTI2022

L0 Data from the 2018 NGEE Arctic LiDAR and Imagery Unoccupied Aerial System Campaign at the Teller 47 Field Site, Seward Peninsula, Alaska

Airborne remote sensing data collected from Los Alamos National Laboratory's (LANL) heavy-lift unoccupied aerial system (UAS) hexacopter platform operated by NGEE Arctic scientists from EES-14 (Earth System Observations group) at Los Alamos National Laboratory. These data were collected in July 2018 at a field site near mile marker 47 along the Teller road between Nome, Alaska and Teller, Alaska. A DJI Matrice 600 Pro Airframe and Routescene UAV LiDARSystem was used to collect LiDAR data, and DJI Phantom 4 Advanced was used to collect optical red/green/blue (RGB) imagery at regular intervals along 11 flight paths. This data package contains unprocessed data products (processing level 0) including flight paths, raw photos, and raw lidar data files (*.kml, *.jpg, and *.lpd formats). Ancillary aircraft data, flight mission parameters, and general flight conditions are also included (see Supplemental Files, *.rinex, and *.rtcm3 files). The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

L0 Data from the 2018 NGEE Arctic LiDAR and Imagery Unoccupied Aerial System Campaign at the Teller 27 Field Site, Seward Peninsula, Alaska

Airborne remote sensing data collected from Los Alamos National Laboratory's (LANL) heavy-lift unoccupied aerial system (UAS) hexacopter platform operated by NGEE Arctic scientists from the EES-14 group at Los Alamos National Laboratory. These data were collected in July 2018 at a field site near mile marker 27 along the Teller road between Nome, Alaska and Teller, Alaska. A DJI Matrice 600 Pro Airframe and Routescene UAV LiDARSystem was used to collect LiDAR data along 12 flight paths, and DJI Phantom 4 Advanced was used to collect optical red/green/blue (RGB) imagery at regular intervals along 5 flight paths. This data package contains unprocessed data products (processing level 0) including flight paths, raw photos, and raw lidar data files (*.kml, *.jpg, and *.lpd formats). Ancillary aircraft data, flight mission parameters, and general flight conditions are also included (see Supplemental Files, *.rinex, and *.rtcm3 files). NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.- The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1995

Characteristics of the HYDICE sensor

In 1992, in an effort to significantly improve knowledge in the field of hyperspectral imagery, the Naval Research Laboratories defined a set of requirements for a new generation sensor. Construction of this instrument, designated HYDICE, has recently been completed at Hughes Danbury Optical Systems. It is currently being flight tested on a Convair 580 operated by ERIM. This paper reports on some of the performance parameters measured to date. The majority of these are derived from laboratory test data. Optomechanical parameters include MTF, spatial co-registration, 'smile', spectral profile and spectral calibration. Detector-related parameters include system responsivity, signal to noise ratio, radiometric stability and gain linearity. The results are compared with the original system performance predictions.

Basedow, R. W.↗
NASA NTRS2005

Software Would Largely Automate Design of Kalman Filter

Embedded Navigation Filter Automatic Designer (ENFAD) is a computer program being developed to automate the most difficult tasks in designing embedded software to implement a Kalman filter in a navigation system. The most difficult tasks are selection of error states of the filter and tuning of filter parameters, which are timeconsuming trial-and-error tasks that require expertise and rarely yield optimum results. An optimum selection of error states and filter parameters depends on navigation-sensor and vehicle characteristics, and on filter processing time. ENFAD would include a simulation module that would incorporate all possible error states with respect to a given set of vehicle and sensor characteristics. The first of two iterative optimization loops would vary the selection of error states until the best filter performance was achieved in Monte Carlo simulations. For a fixed selection of error states, the second loop would vary the filter parameter values until an optimal performance value was obtained. Design constraints would be satisfied in the optimization loops. Users would supply vehicle and sensor test data that would be used to refine digital models in ENFAD. Filter processing time and filter accuracy would be computed by ENFAD.

Chuang, Jason C. H.↗
NASA NTRS1972

Digest of NASA earth observation sensors

A digest of technical characteristics of remote sensors and supporting technological experiments uniquely developed under NASA Applications Programs for Earth Observation Flight Missions is presented. Included are camera systems, sounders, interferometers, communications and experiments. In the text, these are grouped by types, such as television and photographic cameras, lasers and radars, radiometers, spectrometers, technology experiments, and transponder technology experiments. Coverage of the brief history of development extends from the first successful earth observation sensor aboard Explorer 7 in October, 1959, through the latest funded and flight-approved sensors under development as of October 1, 1972. A standard resume format is employed to normalize and mechanize the information presented.

Drummond, R. R.↗
NASA NTRS1984

Platinum thin film resistors as accurate and stable temperature sensors

The measurement characteristics of thin-Pt-film temperature sensors fabricated using advanced methods are discussed. The limitations of wound-wire Pt temperature sensors and the history of Pt-film development are outlined, and the commonly used film-deposition, structuring, and trimming methods are presented in a table. The development of a family of sputtered film resistors is described in detail and illustrated with photographs of the different types. The most commonly used tolerances are reported as + or - 0.3 C + 0.5 percent of the temperature measured.

Diehl, W.↗
NASA NTRS1985

Evaluation of a fault tolerant system for an integrated avionics sensor configuration with TSRV flight data

The performance analysis results of a fault inferring nonlinear detection system (FINDS) using sensor flight data for the NASA ATOPS B-737 aircraft in a Microwave Landing System (MLS) environment is presented. First, a statistical analysis of the flight recorded sensor data was made in order to determine the characteristics of sensor inaccuracies. Next, modifications were made to the detection and decision functions in the FINDS algorithm in order to improve false alarm and failure detection performance under real modelling errors present in the flight data. Finally, the failure detection and false alarm performance of the FINDS algorithm were analyzed by injecting bias failures into fourteen sensor outputs over six repetitive runs of the five minute flight data. In general, the detection speed, failure level estimation, and false alarm performance showed a marked improvement over the previously reported simulation runs. In agreement with earlier results, detection speed was faster for filter measurement sensors soon as MLS than for filter input sensors such as flight control accelerometers.

Caglayan, A. K.↗
NASA NTRS2006

Sensor Management for Applied Research Technologies (SMART)-On Demand Modeling (ODM) Project

NASA requires timely on-demand data and analysis capabilities to enable practical benefits of Earth science observations. However, a significant challenge exists in accessing and integrating data from multiple sensors or platforms to address Earth science problems because of the large data volumes, varying sensor scan characteristics, unique orbital coverage, and the steep learning curve associated with each sensor and data type. The development of sensor web capabilities to autonomously process these data streams (whether real-time or archived) provides an opportunity to overcome these obstacles and facilitate the integration and synthesis of Earth science data and weather model output. A three year project, entitled Sensor Management for Applied Research Technologies (SMART) - On Demand Modeling (ODM), will develop and demonstrate the readiness of Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) capabilities that integrate both Earth observations and forecast model output into new data acquisition and assimilation strategies. The advancement of SWE-enabled systems (i.e., use of SensorML, sensor planning services - SPS, sensor observation services - SOS, sensor alert services - SAS and common observation model protocols) will have practical and efficient uses in the Earth science community for enhanced data set generation, real-time data assimilation with operational applications, and for autonomous sensor tasking for unique data collection.

Goodman, M.↗
NASA NTRS2007

The Sensor Management for Applied Research Technologies (SMART) Project

NASA seeks on-demand data processing and analysis of Earth science observations to facilitate timely decision-making that can lead to the realization of the practical benefits of satellite instruments, airborne and surface remote sensing systems. However, a significant challenge exists in accessing and integrating data from multiple sensors or platforms to address Earth science problems because of the large data volumes, varying sensor scan characteristics, unique orbital coverage, and the steep "learning curve" associated with each sensor, data type, and associated products. The development of sensor web capabilities to autonomously process these data streams (whether real-time or archived) provides an opportunity to overcome these obstacles and facilitate the integration and synthesis of Earth science data and weather model output.

Goodman, Michael↗